Recently, bots or bot scum are becoming an increasingly important issue in a field of online game. Bots are software applications that run automated tasks instead of a user in an online game. The bots give unfair advantages to users using them, and are considered as cheating. Accordingly, from the perspective of a game server, bots are not desired. Use of bot results in huge game imbalances and is very bothersome for honest game players who want to play the game fairly. Players are thus discouraged from keeping paying subscription fees for online game, which naturally threatens game providers' profits.
To fight this scourge, game providers must react quickly to bots' evolution so as to limit their spread while avoiding wrongly accusing human players of cheating of bots. Many strategies have been suggested for anti-bot defense.
Game providers often use repeated Turing tests including CAPTCHA (Completely Automated Public Turing tests tell Computers and Humans Apart) and human controls, which exhibit very accurate decision and reasonable deployment requirements. However, in response to the Turing test, a bot capable of calling an actual user has been developed.
There is another common method of installing software on client machines to prevent bot use, but it is helpless against well-designed bots.
On the other hand, academic researchers are interested in understanding characteristics of specific acts of bots and human beings. These scientific approaches bring forth a method for automatically detecting a bot. Each approach focuses on some theoretical understanding or specific rationale, rather than comprehensive real-time defense strategies. Also, because of lack of complexity and scalability, it is difficult that the above approaches are adapted to actual systems. For example, though a traffic analysis approach provides low time complexity and good results, it cannot be performed online. An I/O device event sequence analysis approach has strong performance, but is impractical.